On this Thanksgiving day when many of our tables—both in our homes and in countless shelters, food pantries, and other community organizations—put forth an abundance of food, it’s an opportune time to reflect on the larger issues surrounding the production, consumption, and sadly the waste of food worldwide.
An estimated 821 million people, or approximately one out of nine people in the world, are undernourished. And one-third of all food produced in the world is wasted, which costs over $1 trillion a year, and produces more greenhouse gas emissions than every country except the U.S. and China.
In my role as Vice Chair & Principal Faculty of Global Grand Challenges at Singularity University, I think about these realities every day and how we might address them. At SU, we believe it is possible to solve the world’s global grand challenges (GGCs) using exponential technologies. Because exponential technologies dramatically fall in cost while increasing in performance, they can help us create an abundance of food, water, shelter, energy, health care, learning opportunities, security, and more.
Furthermore, exponential technologies also significantly lower the cost of entrepreneurship, allowing billions of new business and social entrepreneurs to address these problems, increasing innovation and breaking poverty traps. I’m proud that I get to work with many talented entrepreneurs who are creating novel solutions to our world’s most urgent challenges.
As we celebrate this Thanksgiving holiday, I invite you to explore a few ways that exponential technologies are helping us get closer to that abundant state we’re striving to reach. In my article, “Thanksgiving Food for Thought: The Tech Helping Make Food Abundant,” I outline some fascinating and encouraging solutions being developed that can help us accelerate our progress.
If you’re already building a solution that could help solve a GGC using exponential technologies, I hope you’ll consider applying to our Global Startup Program to start making an impact at the billion scale.